Level

Back Market

Senior Data Scientist ( Economist) - Supply

Back Market is hiring a Senior Data Scientist ( Economist) - Supply in Paris, France. Level rates it ; you can apply on Back Market.

Level's read on this job

  • Level rates this data scientist role Little AI ●○○○: aI is not part of the work.
  • Some of the work can be done remotely, according to the posting.
  • The posting mentions SQL, Python and R among its tools and skills.
  • Level classes it as a senior role.
  • Back Market has 32 other open roles on Level.

AI in this role

Marketplace economics expert using advanced analytics and causal inference to tackle strategic questions around supply and pricing.

sqlpythonrdbttableau
causal-inferenceeconometricsstatisticsexperimentation

Hi, we’re Back Market.

We’re here to help make tech reliable, affordable, and better than new. We're a global marketplace for refurbished devices, helping lower our collective environmental impact by providing trustworthy, affordable tech with 92% less carbon emissions than new.

Yep, you read that right. Turns out refurbished tech is way better for the planet than new. In fact, With every device purchased on Back Market, our positive impact on the planet grows. From our Customer Care representatives to our software engineer, every individual at Back Market cuts the planet — and consumers — a break. Our mission is simple: to do more with what we already have.

Are you ready to join us?

About the Role

You'll be our marketplace economics expert, using advanced analytics and causal inference to tackle our biggest strategic questions. Where will growth come from next? How does competition shape our pricing? Which incentives unlock more supply? How do inventory levels affect customer experience?

Your insights will directly influence decisions across our Supply and Pricing teams, helping shape how we operate in markets around the world.

What You'll Do

  • Build causal inference models to understand the drivers of supply, pricing and assess the impact of our marketplace policies and pricing initiatives

  • Design and analyse experiments and quasi-experiments, including holdout groups, treatment effects and cannibalisation analysis.

  • Translate analytical findings into actionable recommendations, decision tools and guardrails for Revenue, Pricing and Supply teams.

  • Lead cross-functional projects with Supply, Pricing, Business and Engineering teams.

  • Establish best practices for causal inference, experimentation and impact measurement, and mentor other analysts.

  • Communicate complex analytical work clearly to senior stakeholders and influence commercial decisions.

    What You Bring

    • 4-8+ years applying causal inference and statistical methods to business problems

    • Advanced SQL & Python (and/or R)

    • Experience driving strategic decisions through cross-functional collaboration

     

    Bonus Points

    • Digital marketplace, e-commerce, or two-sided platform background

    • Track record building analytics capabilities in growing organizations

    • Experience with dbt and Tableau

      ** We encourage you to apply even if you don't meet every requirement listed above. We value diverse experiences and are committed to helping you grow in areas where you may have less experience.

      Interview Process

      • Initial TA Screening - Marie or Benjamin , 45 min

      • Technical Interview (Live Challenge) - 60 min

      • Leadership Interview - 45 min

      • Stakeholders Discussion - 45 min

      • Cultural Fit - 45 min

WHY SHOULD YOU JOIN US ? ✌🏼

At Back Market, we’re committed to hiring and supporting diverse teams of people from all backgrounds, experiences, and perspectives — it’s one of the reasons we’re such a high-scoring certified B Corp company (93.2).

No matter your role and seniority level, you’ll enjoy impact-driven work with hands-on career development in an innovative, driven, and fast-paced environment — with benefits to match, like:

- A mission driven work environment where your day to day makes an impact on the planet. Seriously.

- Hybrid work environment, with 2 remote days a week and 1 remote work week per quarter, plus 3 flex days.

- Employee Resource Groups, including mentorship programs, comprehensive accessibility policies, and cultural competency training.

At Back Market, we strive to create a workplace that embodies the world we’re trying to change. We’ve embedded our diversity, equity, and inclusion principles into our DNA — from dedicated staff to employee resource groups to our company values.

We know that the perfect background for a role doesn’t mean the perfect fit — we encourage you to apply for a role even if you think you may not have all the qualifications.

If reasonable accommodations are needed for the interview process, please do not hesitate to discuss this with the Talent Acquisition Team.

How we rate this

Senior Data Scientist ( Economist) - Supply at Back Market rates 25 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Causal InferenceEconometricsStatisticsExperimentationSQLPythonRdbt

Also common in data scientist jobs at this level

Pay

Typical data scientist job
$166k

This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs

Questions you could be asked

  1. Tell me about a project where causal inference was part of your work. What did you do?
  2. Tell me about a project where econometrics was part of your work. What did you do?
  3. Tell me about a project where statistics was part of your work. What did you do?
  4. Tell me about a project where experimentation was part of your work. What did you do?
  5. Walk me through how you've used SQL in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Causal Inference, Econometrics, Statistics, Experimentation, and SQL. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

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